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Software Engineer with Generative AI
"Software Engineer with Generative AI" is a comprehensive, practical, and accessible guide designed to equip the modern software engineer with the skills and knowledge required to build the next generation of intelligent applications. This book serves as a bridge between traditional software development and the cutting-edge field of Generative AI, providing a structured pathway from fundamental concepts to advanced, real-world implementation.
Key
1. Beginner to Advanced The book starts with the absolute basics, assuming no prior AI knowledge, and gradually builds up to advanced topics like fine-tuning, Retrieval-Augmented Generation (RAG), and LLMOps, making it suitable for a wide range of learners.
2. Practical Hands-On Learning is reinforced through numerous code examples, hands-on exercises, and step-by-step tutorials using popular libraries and platforms like Python, OpenAI, Hugging Face, and LangChain.
3. Simple and Clear Complex technical jargon is broken down into simple, easy-to-understand explanations, supplemented with real-life analogies and practical examples to solidify understanding.
4. End-to-End Capstone The final chapter is a complete, do-it-yourself (DIY) project where readers build a fully functional AI application, including complete source code and a detailed, step-by-step implementation guide.
5. Focus on Software Engineering This is not just an AI book; it's a software engineering book. It covers architecture design, the GenAI-SDLC, testing strategies, deployment, and operational best practices (LLMOps).
6. Real-World Case Integrated case studies showcase how Generative AI is being applied in industries today, providing context and inspiration.
7. Emphasis on Responsible A dedicated section covers the critical topics of ethics, bias, fairness, and security in AI systems, preparing students to be responsible technologists.
To Whom This Book Is
1. B.Tech/M.Tech Computer Science An ideal textbook that covers the core syllabus requirements for courses on AI, Machine Learning, and Application Development.
2. Aspiring AI/ML A perfect starting point and practical guide for those looking to specialize in the field of Generative AI.
3. Software Developers and A crucial upskilling resource for professionals seeking to integrate Generative AI capabilities into their products and workflows.
4. Educators and A well-structured resource for teaching courses on AI application development, complete with examples and a project blueprint.
5. Tech Enthusiasts and Anyone curious about building practical applications with the latest AI technologies.
This book is designed to be a journey. We begin with the absolute fundamentals, building a solid foundation for those new to the field. We then progressively move through the essential skills of a Generative AI mastering prompt engineering, architecting intelligent systems, integrating and fine-tuning models, and leveraging powerful frameworks like LangChain. The journey culminates in a comprehensive, hands-on capstone project where you will build a complete, functional application from scratch, applying the knowledge you've accumulated throughout the book.
Key
1. Beginner to Advanced The book starts with the absolute basics, assuming no prior AI knowledge, and gradually builds up to advanced topics like fine-tuning, Retrieval-Augmented Generation (RAG), and LLMOps, making it suitable for a wide range of learners.
2. Practical Hands-On Learning is reinforced through numerous code examples, hands-on exercises, and step-by-step tutorials using popular libraries and platforms like Python, OpenAI, Hugging Face, and LangChain.
3. Simple and Clear Complex technical jargon is broken down into simple, easy-to-understand explanations, supplemented with real-life analogies and practical examples to solidify understanding.
4. End-to-End Capstone The final chapter is a complete, do-it-yourself (DIY) project where readers build a fully functional AI application, including complete source code and a detailed, step-by-step implementation guide.
5. Focus on Software Engineering This is not just an AI book; it's a software engineering book. It covers architecture design, the GenAI-SDLC, testing strategies, deployment, and operational best practices (LLMOps).
6. Real-World Case Integrated case studies showcase how Generative AI is being applied in industries today, providing context and inspiration.
7. Emphasis on Responsible A dedicated section covers the critical topics of ethics, bias, fairness, and security in AI systems, preparing students to be responsible technologists.
To Whom This Book Is
1. B.Tech/M.Tech Computer Science An ideal textbook that covers the core syllabus requirements for courses on AI, Machine Learning, and Application Development.
2. Aspiring AI/ML A perfect starting point and practical guide for those looking to specialize in the field of Generative AI.
3. Software Developers and A crucial upskilling resource for professionals seeking to integrate Generative AI capabilities into their products and workflows.
4. Educators and A well-structured resource for teaching courses on AI application development, complete with examples and a project blueprint.
5. Tech Enthusiasts and Anyone curious about building practical applications with the latest AI technologies.
This book is designed to be a journey. We begin with the absolute fundamentals, building a solid foundation for those new to the field. We then progressively move through the essential skills of a Generative AI mastering prompt engineering, architecting intelligent systems, integrating and fine-tuning models, and leveraging powerful frameworks like LangChain. The journey culminates in a comprehensive, hands-on capstone project where you will build a complete, functional application from scratch, applying the knowledge you've accumulated throughout the book.
383 pages, Kindle Edition
Published October 21, 2025
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